Scaling AI with Confidence: The Case for Human-in-the-Loop (HITL) Data Annotation
The promise of AI at scale is compelling: faster decisions, broader reach, lower operational cost. But scale amplifies everything — including mistakes. A model that misclassifies 1% of cases in a test environment might process ten thousand decisions a day in production. That 1% is now a hundred daily errors. In healthcare, finance, legal, or […]
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